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Add Flag to PeftLoraLoaderMixinTests to Enable/Disable Text Encoder LoRA Tests #12962

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Add Flag to PeftLoraLoaderMixinTests to Enable/Disable Text Encoder LoRA Tests #12962

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51dc061
Improve incorrect LoRA format error message
dg845 Jan 10, 2026
dc43efb
Add flag in PeftLoraLoaderMixinTests to disable text encoder LoRA tests
dg845 Jan 10, 2026
bd91810
Merge branch 'main' into improve-lora-loaders
dg845 Jan 10, 2026
0b10746
Apply changes to LTX2LoraTests
dg845 Jan 10, 2026
23db559
Merge branch 'main' into improve-lora-loaders
sayakpaul Jan 12, 2026
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38 changes: 19 additions & 19 deletions src/diffusers/loaders/lora_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -214,7 +214,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")
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@sayakpaul sayakpaul Jan 12, 2026

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Suggested change
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `"lora"` substring.")


self.load_lora_into_unet(
state_dict,
Expand Down Expand Up @@ -641,7 +641,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_unet(
state_dict,
Expand Down Expand Up @@ -1081,7 +1081,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -1377,7 +1377,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -1659,7 +1659,7 @@ def load_lora_weights(
)

if not (has_lora_keys or has_norm_keys):
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

transformer_lora_state_dict = {
k: state_dict.get(k)
Expand Down Expand Up @@ -2506,7 +2506,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -2703,7 +2703,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -2906,7 +2906,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -3333,7 +3333,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -3536,7 +3536,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -3740,7 +3740,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -3940,7 +3940,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -4194,7 +4194,7 @@ def load_lora_weights(
)
is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

load_into_transformer_2 = kwargs.pop("load_into_transformer_2", False)
if load_into_transformer_2:
Expand Down Expand Up @@ -4471,7 +4471,7 @@ def load_lora_weights(
)
is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

load_into_transformer_2 = kwargs.pop("load_into_transformer_2", False)
if load_into_transformer_2:
Expand Down Expand Up @@ -4691,7 +4691,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -4894,7 +4894,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -5100,7 +5100,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -5306,7 +5306,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down Expand Up @@ -5509,7 +5509,7 @@ def load_lora_weights(

is_correct_format = all("lora" in key for key in state_dict.keys())
if not is_correct_format:
raise ValueError("Invalid LoRA checkpoint.")
raise ValueError("Invalid LoRA checkpoint. Make sure all LoRA param names contain `lora`.")

self.load_lora_into_transformer(
state_dict,
Expand Down
22 changes: 2 additions & 20 deletions tests/lora/test_lora_layers_auraflow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,8 @@ class AuraFlowLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
text_encoder_target_modules = ["q", "k", "v", "o"]
denoiser_target_modules = ["to_q", "to_k", "to_v", "to_out.0", "linear_1"]

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 8, 8, 3)
Expand Down Expand Up @@ -114,23 +116,3 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
@unittest.skip("Not supported in AuraFlow.")
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in AuraFlow.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in AuraFlow.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in AuraFlow.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in AuraFlow.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in AuraFlow.")
def test_simple_inference_with_text_lora_save_load(self):
pass
22 changes: 2 additions & 20 deletions tests/lora/test_lora_layers_cogvideox.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,8 @@ class CogVideoXLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):

text_encoder_target_modules = ["q", "k", "v", "o"]

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 9, 16, 16, 3)
Expand Down Expand Up @@ -147,26 +149,6 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogVideoX.")
def test_simple_inference_with_text_lora_save_load(self):
pass

@unittest.skip("Not supported in CogVideoX.")
def test_simple_inference_with_text_denoiser_multi_adapter_block_lora(self):
pass
22 changes: 2 additions & 20 deletions tests/lora/test_lora_layers_cogview4.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -85,6 +85,8 @@ class CogView4LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
"text_encoder",
)

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 32, 32, 3)
Expand Down Expand Up @@ -162,23 +164,3 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
@unittest.skip("Not supported in CogView4.")
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogView4.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogView4.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogView4.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogView4.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in CogView4.")
def test_simple_inference_with_text_lora_save_load(self):
pass
22 changes: 2 additions & 20 deletions tests/lora/test_lora_layers_flux2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,8 @@ class Flux2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
text_encoder_cls, text_encoder_id = Mistral3ForConditionalGeneration, "hf-internal-testing/tiny-mistral3-diffusers"
denoiser_target_modules = ["to_qkv_mlp_proj", "to_k"]

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 8, 8, 3)
Expand Down Expand Up @@ -146,23 +148,3 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
@unittest.skip("Not supported in Flux2.")
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in Flux2.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in Flux2.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in Flux2.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in Flux2.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in Flux2.")
def test_simple_inference_with_text_lora_save_load(self):
pass
22 changes: 2 additions & 20 deletions tests/lora/test_lora_layers_hunyuanvideo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,8 @@ class HunyuanVideoLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
"text_encoder_2",
)

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 9, 32, 32, 3)
Expand Down Expand Up @@ -172,26 +174,6 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in HunyuanVideo.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in HunyuanVideo.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in HunyuanVideo.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in HunyuanVideo.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in HunyuanVideo.")
def test_simple_inference_with_text_lora_save_load(self):
pass


@nightly
@require_torch_accelerator
Expand Down
26 changes: 2 additions & 24 deletions tests/lora/test_lora_layers_ltx2.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -150,6 +150,8 @@ class LTX2LoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):

denoiser_target_modules = ["to_q", "to_k", "to_out.0"]

supports_text_encoder_loras = False

@property
def output_shape(self):
return (1, 5, 32, 32, 3)
Expand Down Expand Up @@ -267,27 +269,3 @@ def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(se
@unittest.skip("Not supported in LTX2.")
def test_modify_padding_mode(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_with_partial_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_with_text_lora(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_with_text_lora_and_scale(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_with_text_lora_fused(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_with_text_lora_save_load(self):
pass

@unittest.skip("Text encoder LoRA is not supported in LTX2.")
def test_simple_inference_save_pretrained_with_text_lora(self):
pass
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